POS0710 METABOLIC INFLAMMATORY VOLUME AND TOTAL INFLAMMATORY GLYCOLYSIS: NOVEL PARAMETERS TO EVALUATE DISEASE ACTIVITY ON PET-CT IN TAKAYASU ARTERITIS
Authors: M. Ora, D. P. Misra, C. Kavadichanda, K. Singh, U. Rathore, N. Jain, V. Agarwal, S. Gamhbir
Journal: Annals of the Rheumatic Diseases (2023)

<h3>Background</h3> 18-fluorodeoxyglucose (FDG) Positron emission tomography-computed tomography (PET-CT) has only moderate concordance with C-reactive protein (CRP) in Takayasu arteritis (TAK). <h3>Objectives</h3> We propose and evaluate the diagnostic accuracy of two new PET-CT parameters, metabolic inflammatory volume (MIV) and total inflammatory glycolysis (TIG) to quantify arterial FDG uptake for active TAK. <h3>Methods</h3> Images of PET-CT of TAK were reviewed to calculate mean standardized uptake value (SUV<sub>mean</sub>) and maximum standardized uptake value (SUV<sub>max</sub>), target-to-blood pool ratio (TBR), target-to-liver ratio (TLR), and PET Vasculitis Activity Score (PETVAS) [1]. ESR, CRP, disease activity [using physician global assessment (PGA, active/inactive), Indian TAK Clinical Activity Score 2010 (ITAS2010), ITAS2010 with ESR (ITAS-A-ESR) or CRP (ITAS-A-CRP), Disease Extent Index in TAK (DEI.TAK)] were extracted from clinic files. Regions of interest (ROI) were drawn to calculate MIV in areas of FDG uptake ≥1.5-times SUV<sub>max</sub> on syngo.via. MIV was semiautomatically calculated after excluding areas of physiological tracer uptake. TIG was calculated by multiplying MIV with SUV<sub>mean</sub>. MIV and TIG for all areas of arterial FDG uptake were added. Area under the receiver operating characteristics (ROC) curves (AUC, with 95%CI) to predict active disease using PGA with absolute values of SUV<sub>max</sub>, SUV<sub>mean</sub>, TBR, TLR, MIV, TIG, PETVAS, CRP, ESR, ITAS2010, ITAS-A-ESR, ITAS-A-CRP, and DEITAK were calculated. Dichotomized cut-offs for active disease [PETVAS ≥5.5 [2],≥10,≥15,or≥20 [1]; CRP≥6 mg/L; ESR≥40 mm/hr; for the remaining parameters, cut-offs correctly classifying disease activity in most patients) were used to calculate sensitivity, specificity, likelihood ratio of a positive test (LR+), likelihood ratio of a negative test (LR-), positive predictive value (PPV), negative predictive value (NPV), and AUC (with 95%CI).Concordance between CRP and PET-CT parameters were assessing kappa statistic. Analyses were performed using STATA 16.1 I/C. <h3>Results</h3> PET-CT of 30 TAK [mean (SD) age 29.9 (11.5) years, 22 females, 29 immunosuppressive-naive) were reviewed. AUC using absolute values ranged between 0.852 to 0.926 (Figure 1). Using dichotomized optimal cut-offs for SUV<sub>max</sub>, SUV<sub>mean</sub>, TBR, TLR, MIV, and TIG, MIV and TIG performed better than SUV<sub>max</sub>, SUV<sub>mean</sub>, TBR, TLR, PETVAS (at cut-offs 5.5, 10, and 15 – none had PETVAS≥20) to detect active TAK (Table 1). Agreement with CRP for active TAK was similar for MIV (70%) and TIG (70%) with SUV<sub>max</sub>, SUV<sub>mean</sub>, TBR, and TLR (each 66.67%), and better than PETVAS [≥5.5 (56.67%), ≥10 (50%), ≥15 (40%), ≥40 (40%)]. <h3>Conclusion</h3> Novel PET-CT parameters, MIV and TIG, had comparable performance to established PET-CT parameters and better performance than PETVAS for active TAK, and require further exploration in LVV. <h3>References</h3> [1]Grayson PC, et al. Arthritis Rheumatol 2018;70(3):439-49. [2]Tahra SK, et al. Turk J Med Sci. 2022;52(2):313-22. <h3>Acknowledgements:</h3> NIL. <h3>Disclosure of Interests</h3> None Declared.